JITL-MBN: A Real-Time Causality Representation Learning for Sensor ...
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May 13, 2022 · A real-time causality representation learning based on just-in-time learning (JITL) and modular Bayesian network (MBN) is proposed to diagnose its sensor ...
The method of training local model online requires high speed, and MBN alleviates the problem of slow real-time modeling speed. V. CONCLUSION. A sensor fault ...
et al. JITL-MBN: A real-time causality representation learning for sensor fault diagnosis of traction drive system in high-speed trains. IEEE Trans. Neural ...
... JITL-MBN: A real-time causality representation learning for sensor fault diagnosis of traction drive system in high-speed trains, IEEE Trans. Neural Netw ...
Overview of fault prognosis for traction systems in high-speed trains - OUCI
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Chen, JITL-MBN: A real-time causality representation learning for sensor fault diagnosis of traction drive system in high-speed trains, IEEE Trans. Neural ...
JITL-MBN: A Real-Time Causality Representation Learning for Sensor Fault Diagnosis of Traction Drive System in High-Speed Trains. Article. May 2022.
et al. Jitl-MBN: A real-time causality representation learning for sensor fault diagnosis of traction drive system in high-speed trains. IEEE Transactions on ...
JITL-MBN: A Real-Time Causality Representation Learning for Sensor Fault Diagnosis of Traction Drive System in High-Speed Trains. Article. May 2022.
JITL-MBN: A realtime causality representation learning for sensor fault diagnosis of traction drive system in high-speed trains. IEEE Trans. Neural Netw ...
Exploring real-time fault detection of high-speed train traction motor based on machine learning and wavelet analysis. Neural Computing & Applications, 34 ...